On the model and optimization algorithm for dynamic team orienteering problem

A dynamic team orienteering problem of partial dynamic arrival customers is studied, and a model of the problem is established to deal with the team orienteering problem, which is one of the most critical problems in the optimization design for logistic distribution system. The dynamic problem is converted into a series of static sub-problems by partitioning the planning horizon into a series of time segments. An ant colony optimization (ACO) based algorithm is proposed to solve the resulting problem. The prominent characteristic of the algorithm is to use the information obtained from the last time segment to enhance the search behavior. An exact offline algorithm based on branch and price is also presented to solve the problem. Experimental results and comparisons with the exact offline algorithm based on the branch and bound show that the proposed ACO-based algorithm can solve four test instances within 1000 seconds, and that the solutions of two test instances obtained by the proposed ACO-based algorithm are better than those obtained by the exact offline algorithm.